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Fix most of ZeRO stage uses optimizer partitioning

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- we have to prepare optimizer and ds_model at the same time.
 - pull/1139#issuecomment-1986790007

Signed-off-by: BootsofLagrangian <hard2251@yonsei.ac.kr>
This commit is contained in:
BootsofLagrangian
2024-03-20 20:52:59 +09:00
parent fbb98f144e
commit d9456020d7
1 changed files with 5 additions and 3 deletions
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8
sdxl_train.py
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@@ -412,7 +412,10 @@ def train(args):
text_encoder1=text_encoder1 if train_text_encoder1 else None,
text_encoder2=text_encoder2 if train_text_encoder2 else None,
)
ds_model = accelerator.prepare(ds_model)
# most of ZeRO stage uses optimizer partitioning, so we have to prepare optimizer and ds_model at the same time. # pull/1139#issuecomment-1986790007
ds_model, optimizer, train_dataloader, lr_scheduler = accelerator.prepare(
ds_model, optimizer, train_dataloader, lr_scheduler
)
training_models = [ds_model]
else:
@@ -423,8 +426,7 @@ def train(args):
text_encoder1 = accelerator.prepare(text_encoder1)
if train_text_encoder2:
text_encoder2 = accelerator.prepare(text_encoder2)
optimizer, train_dataloader, lr_scheduler = accelerator.prepare(optimizer, train_dataloader, lr_scheduler)
optimizer, train_dataloader, lr_scheduler = accelerator.prepare(optimizer, train_dataloader, lr_scheduler)
# TextEncoderの出力をキャッシュするときにはCPUへ移動する
if args.cache_text_encoder_outputs: